Lead Data Engineer

Role Overview

We are seeking an accomplished Lead Data Engineer (SFIA Level 5) to provide technical leadership, direction, and strategy across complex data engineering initiatives. This role involves leading teams to deliver resilient, scalable, and standards-driven data solutions, while engaging with senior stakeholders to translate requirements into robust data products and services.

The Lead Data Engineer will be responsible for setting engineering standards, embedding best practices, and ensuring delivery aligns with strategic principles. The role also carries line management responsibilities, helping to build capability within the engineering community.

Key Responsibilities

• Provide technical leadership and set the direction for engineering teams and communities, ensuring delivery adheres to data standards and strategic principles.

• Engage with senior stakeholders to define requirements for complex and sensitive data products, pipelines, and platforms.

• Oversee delivery and user testing of requirements across teams.

• Lead the redevelopment of existing data journeys, enhancing performance, resilience, and scalability, while adapting to evolving systems, tools, and platforms.

• Translate user requirements and data designs into effective, reusable, and standards-compliant data solutions.

• Define, deliver, and embed engineering standards across multiple platforms, keeping them updated and ensuring adherence across teams.

• Champion data validation methods and standards to ensure data quality from source to consumption.

• Standardise code, product, and service quality across engineering teams by implementing best practices and governance.

• Design and promote reusable metadata libraries and cross-business standards in collaboration with other technical disciplines.

• Partner with Lead Data Engineers, Data Architects, and Technologists to design and develop innovative solutions.

• Continually improve data engineering, automation, and scaling capabilities.

• Provide leadership and mentoring, helping to develop the skills and capabilities of the Data Engineer community.

• Carry out line management responsibilities, supporting the growth and development of Data Engineers.

• Ensure alignment and collaboration with teams across Digital Group, Data & Analytics, and Data Practice for consistency and scalability.

Skills & Experience Required

Practitioner Level:

• Proven ability to lead development and delivery of complex data pipelines using big data technologies (Apache Kafka, Spark, or similar) and cloud platforms (AWS, Azure).

• Technical leadership experience, setting team direction and ensuring adherence to data standards and strategic principles.

• Strong programming/coding expertise across Python, SQL, Proc SQL, and cloud technologies (Azure stack, AWS).

• Experience in designing and executing data/code quality assurance processes, troubleshooting, and resolving processing issues.

• Ability to apply standards and tools to design, code, test, correct, and document programs/scripts from agreed specifications.

• Knowledge of data modelling, with experience leading strategies for delivery to wider communities.

Expert Level:

• Proven track record leading the development of ETL pipelines for large, complex, or high-volume datasets, with effective delegation and oversight.

• Advanced knowledge of data engineering standards, with the ability to establish, maintain, and enforce them across teams.